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Xiaole Wang, Jiwei Qin, Shangju Deng and Wei Zeng
In recent years, the application of knowledge graphs to alleviate cold start and data sparsity problems of users and items in recommendation systems, has aroused great interest. In this paper, in order to address the insufficient representation of user a...
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Yi Liu, Chengyu Yin, Jingwei Li, Fang Wang and Senzhang Wang
Accurately predicting user?item interactions is critically important in many real applications, including recommender systems and user behavior analysis in social networks. One major drawback of existing studies is that they generally directly analyze th...
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Depeng Zhang, Hongchen Wu and Feng Yang
The popularity of intelligent terminals and a variety of applications have led to the explosive growth of information on the Internet. Some of the information is real, some is not real, and may mislead people?s behaviors. Misleading information refers to...
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Ninghua Sun, Tao Chen, Wenshan Guo and Longya Ran
The problems with the information overload of e-government websites have been a big obstacle for users to make decisions. One promising approach to solve this problem is to deploy an intelligent recommendation system on e-government platforms. Collaborat...
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